Peakons of the shallow-water wave equation implementation with PINNs
Year: 2025
Type: conference-paper
Abstract: In this paper, we implement the peakon solution of the CH equation containing highly nonlinear terms using the Physics-Informed Neural Networks, and we define the corresponding neural network models according to different forms of peakon solution expressions. The main implementation is to study the spatio-temporal dynamics behaviour of the peakon solution for the general form of the CH equations. From the experimental results, the Physics-Informed Neural Networks can basically complete the analytical solution prediction of the shallow-water wave equation, and achieve the accurate capture of highly complex nonlinear terms, which proves the successful application of the Physics-Informed Neural Networks method in the peakon solution of the shallow-water wave equation.
Authors: Jianlin Zhang, Yake Leng, Hui Dong, Jianuo Yang, Yinglin Jiao
Institution: Zhongyuan University of Technology
Language: English
Subfield: Statistical and Nonlinear Physics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4408039310